Applied Science PhD Intern

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Science · Artificial Intelligence

In short

As an Applied Science PhD Intern at Microsoft, you will work on innovative AI and machine learning solutions for real-world product scenarios. This role involves analyzing algorithms, developing models like LLMs, and collaborating with teams to bring research into production. You will gain expertise in cutting-edge research areas and contribute to making a tangible impact on product quality and business outcomes.

Responsibilities

Design, implement, and evaluate machine learning and AI solutions for real-world product scenarios.
Analyze and improve the performance of advanced algorithms on large-scale datasets.
Translate business and product challenges into machine learning research problems and experimental frameworks.
Design and execute rigorous experiments to evaluate model effectiveness and drive continuous improvement.
Develop, train, fine-tune, and evaluate machine learning models, including LLMs and SLMs.
Build scalable prototypes and AI-powered systems that can be deployed in production environments.
Prepare, clean, and analyze large datasets while ensuring data quality and integrity.
Develop innovative approaches to model evaluation, benchmarking, and performance optimization.
Collaborate with researchers, engineers, and product teams to bring research breakthroughs into Microsoft products and services.
Document research findings, communicate results, and contribute to technical reports, publications, patents, or open-source initiatives.
Stay informed of current industry trends and emerging research in AI, Machine Learning, and Generative AI.

Requirements

Currently pursuing a PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, Computer Engineering, Econometrics, or a related technical field.
Must have at least one semester/quarter remaining following completion of the internship.
Research experience in Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Generative AI, or related areas.
Strong programming skills in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or equivalent.
Experience designing experiments, analysing results, and applying statistical methods to solve research problems.
Demonstrated ability to formulate hypotheses, conduct independent research, and communicate technical findings effectively.
Experience working with large datasets and building end-to-end machine learning pipelines.

Skills

PythonPyTorchTensorFlowMachine LearningDeep LearningNatural Language ProcessingComputer VisionGenerative AILarge Language ModelsSmall Language Models

#Machine Learning#AI#Data Science#Research#Internship#PhD

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